The present invention relates to a method for improving quality of disparity images, especially to a method for reducing matching errors in disparity images by information in zoom images (images with different focal length).
In the field related improvement of matching errors, there are some prior arts that improve disparity images by using the similar concept available now. For example, refer to U.S. Pat. No. 8,009,897 “Method and apparatus for image matching”, the method and apparatus perform correspondence estimation between pixels of a stereo image pair to obtain matching information for corresponding pixels in each image. To perform a match for a particular pixel in a first image firstly an adaptive curve is constructed about the pixel, being a sequence of connected pixels with similar intensity values to the pixel being matched. Then the curve constructed is used as a matching element within the second image to finds a matching pixel representative of the same 3D scene point in the second image to the particular pixel. Thus accurate disparity maps can be obtained and used in an image synthesis algorithm to produce novel images with improved quality. Refer to U.S. Pat. No. 6,856,314 “Method and system for 3D reconstruction of multiple views with altering search path and occlusion modeling”, the method receives a plurality of image features corresponded between different 2D views of the scene, the corresponded image features deviating between different views as a result of camera relative motion. The method propagates 3D depth information from the confident seeds to neighboring image features, while avoiding image features that have been determined to be occluded views. More information in the disparity image is obtained by a plurality of imaging devices for reducing matching errors of corresponding points. Refer to US Pub. No. 2014/0002605 “Imaging system and method”, the imaging system includes a cross-checking module configured to cross check the disparity map and identify occlusion pixels in the disparity map, and an occlusion-refining module configured to refine the occlusion pixels for improving the disparity image.
For the techniques available now, more image information of the disparity image is obtained by using information in stereo image pairs each of which includes a left image and a right image for matching of corresponding points, or by increasing numbers of cameras to get more image information for reducing matching errors. Among prior arts that use information in a stereo image pair for matching of corresponding points, a common stereo vision algorithm uses information of an image pair captured by two cameras with different viewpoints to compute the matching cost for matching corresponding points and further calculate the disparity between the images. In the above method, the information used for matching only comes from the image pair captured. The matching cost computation based on limited information is easy to cause mismatching of feature points. That means matching errors occur easily when less image information is available.
As to prior arts related to using more cameras to get more image information for reducing matching errors, information in multi-view images captured by a plurality of cameras is aggregated to solve the problem of matching errors occurred in the image pair captured by two cameras respectively. More information in the images obtained is used to check similarity of the corresponding points and find out the most similar points in the reference image and other images. Then the disparity value of the most similar points is estimated. Thereby the percentage of the errors can be reduced by accurate matching in other image pairs even corresponding matching errors occur in one of the image pairs. However, the multi-view system developed for solving the problem of mismatching of the corresponding points has a major disadvantage that a plurality of cameras is required to take pictures. Obviously the hardware cost is increased. Although the matching errors are reduced due to increased image information obtained, the hardware cost is increased owing to more cameras required.
Thus there is room for improvement and there is a need to provide a novel method that gets more image information by zoom function of the camera for reducing matching errors, without increasing the hardware cost.